As a Software Engineer at Softwave Soluzioni & Tecnologie Srl, you are at the heart of our mission to deliver robust, scalable, and high-performance digital solutions. This role is pivotal to our operations, as you will be responsible for designing and implementing complex architectures that directly impact our clients' business success. You won't just be writing code; you will be solving real-world challenges across diverse technology stacks, from AWS-based cloud infrastructure to sophisticated.Net and Java-based enterprise systems. Your work will involve close collaboration with cross-functional teams, requiring you to balance technical excellence with a deep understanding of project requirements. Whether you are building full-stack applications or optimizing cloud-native services, your contributions directly influence the reliability and efficiency of our product offerings. Expect an environment that values technical rigor, continuous learning, and the ability to adapt to evolving project needs across our and hubs. Lombardy Lazio ##### Tip Given our focus on diverse stacks like.Net and Java, ensure your preparation highlights your depth in your primary language while demonstrating a willingness to work across the full development lifecycle.
Initial Screening
reportedGauge your technical background and interest in specific projects.
What to demonstrate
- Gauge your technical background and interest in specific projects
- Depth in .NET
How to prepare
- Be able to walk your CV end to end in two minutes, and say why this company specifically.
- Have your salary expectations, notice period and location constraints ready, and ask for the rest of the loop in writing.
Technical Evaluations
reportedInvolves live coding exercises or in-depth technical discussions about past projects.
What to demonstrate
- Involves live coding exercises or in-depth technical discussions about past projects
- Depth in .NET
How to prepare
- Answer aloud and timed: Describe a challenging bug you encountered in a production environment and your systematic approach to resolving it.
- Answer aloud and timed: How do you ensure code quality and maintainability in a large-scale project?
Team Engagement
reportedOpportunity to engage with team members and leads to understand technical challenges.
What to demonstrate
- Opportunity to engage with team members and leads to understand technical challenges
- Depth in .NET
How to prepare
- Answer aloud and timed: Explain the benefits and trade-offs of using microservices versus monolithic architecture.
- Answer aloud and timed: How would you design a scalable, fault-tolerant web application hosted on AWS?
PracHub editorial advice for the preparation topics above.
Structure your answers
Use the STAR method (Situation, Task, Action, Result) for behavioral questions to keep your responses focused and impactful.
Know your resume
Be prepared to dive deep into any project or technology you have listed. We will ask follow-up questions to verify your depth of understanding.
Ask thoughtful questions
Use the time at the end of the interview to ask about our engineering culture, the challenges our teams are currently facing, and how we support professional development.
Stay calm under pressure
If you get stuck on a coding problem, communicate your thought process out loud. We are often more interested in your problem-solving logic than the perfect syntax.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
How do you handle database connection pooling and thread safety in a high-concurrency environment?
How do you handle database connection pooling and thread safety in a high-concurrency environment?
Approach
- Say what the runtime actually does before reasoning about the code.
- Name what is shared across threads and what owns each piece of state.
- Identify the window where an invariant is briefly untrue.
- Distinguish a value from a reference to it, and say which one you handed out.
Follow-up
- What happens if two callers reach this at the same time?
- Where could this allocate more than you expect?
Collapse a redelivered event batch into per-aggregate high-water marks
You drain a batch of up to 5,000,000 events, each (aggregate_id BIGINT, aggregate_version INT, event_type, payload). The log guarantees order within one aggregate only; the batch merges 64 partitions, and a relay failover has redelivered a range, so an older version for an aggregate can appear after a newer one. Given a map of last_applied_version per aggregate, produce the events worth applying, at most one per (aggregate_id, version), plus the count discarded. Target O(n) time. State the memory for 2,000,000 distinct aggregates and what you do when it does not fit.
Approach
- One pass, one hash map from aggregate_id to the highest version kept, and a discard counter. An event whose version is at or below last_applied_version for its aggregate is dropped without further work, which is the whole reason the event carries its version rather than a delta. O(n) expected time, O(d) space in distinct aggregates.
- Keep the maximum, never the last occurrence. The redelivered range means the final appearance of an aggregate in the batch can be an older version than one seen earlier in the same batch, so last-wins applies stale state over newer state and the projection regresses with no error anywhere.
- Cost the memory instead of calling it large: an 8-byte key plus a 4-byte version is 12 bytes of payload, and an open-addressed table held at a 0.7 load factor costs roughly 17 bytes per entry before per-slot metadata, so 2,000,000 aggregates is tens of megabytes in a native layout and several times that in a runtime that boxes both key and value.
- If the distinct set exceeds memory, partition on hash(aggregate_id) mod P and reduce each partition independently. Every event for one aggregate hashes to the same partition, so the per-partition result is exact and the merge is concatenation rather than a second reduction.
Follow-up
- The payload is a patch rather than a snapshot, so applying only the highest version loses the intermediate changes. What changes in your reduction?
- How do you detect that version 7 arrived while version 6 was never delivered, and what should the consumer do about the gap?
Canonicalise a request body into a stable idempotency fingerprint
idempotency_key.request_fingerprint is a SHA-256 over the method, path and canonicalised body, and a retry whose fingerprint differs must be rejected with 422 rather than served the stored response. Write the canonicaliser. Bodies are JSON up to 256 KB nested at most 32 levels; clients vary key order, whitespace and unicode escaping, and some send 64-bit ids as JSON numbers. Produce a deterministic byte string such that semantically identical bodies match and any semantic difference does not. State your complexity and name two normalisations you refuse to perform.
Approach
- Parse once into a tree, then re-serialise under fixed rules: object keys sorted, array order preserved, one escaping convention, no insignificant whitespace. Parsing is O(n) and sorting keys is O(k log k) per object, so O(n log n) overall with O(depth) stack, and the 32-level cap is enforced during parsing because hostile nesting is how a canonicaliser becomes a stack overflow.
- Sort keys by their UTF-8 bytes and say why the obvious implementation is wrong in some runtimes: a default string comparison that orders by UTF-16 code units places surrogate pairs, meaning code points from U+10000 up, below U+E000 to U+FFFF, which is not UTF-8 byte order, so two services written in different languages disagree on the same document.
- Do not re-encode numbers through a double. IEEE-754 binary64 represents integers exactly only up to 2^53, so normalising a 19-digit id through a float changes it, and 1 against 1.0 cannot be reconciled without deciding whether they are the same value. Preserve the literal token, and require ids as strings at the API boundary if you want them comparable.
- Reject duplicate keys rather than picking one. JSON permits them and parsers disagree, most keeping the last, so any choice you make ties the fingerprint to a parser detail that the code handling the request does not necessarily share.
Follow-up
- A client sends the same logical request with an extra field your API ignores. Same key, different fingerprint, so you return 422. Is that the right answer?
- Where does the fingerprint get computed relative to request decompression and the body-size limit?
Stop tag and share joins from fanning out a page
resource_tag is (resource_id, tag_id) with PK (resource_id, tag_id); resource_share is (resource_id, shared_with_user_id, permission). The tagged-and-shared listing inner-joins resource to both, filters tenant_id, tag_id = ANY($2) and shared_with_user_id = $3, orders by updated_at DESC and takes 50. Pages come back with fewer than 50 distinct resources and the total in the header is far too high. Explain the row multiplication, rewrite both the page query and the count query so each is correct, and name the index each one needs. PostgreSQL 16.
Approach
- Do the arithmetic against the predicates that are actually there. An inner join emits one row per matching child row, and both joins are filtered: tag_id = ANY($2) admits only the requested tags, shared_with_user_id = $3 admits one user's share rows. So a resource holding three of the requested tags and shared with $3 once yields three rows, not one — the multiplier is its count of matching tags times its share rows for that single user, and that second factor is 1 unless the table admits duplicate (resource_id, shared_with_user_id) pairs. LIMIT 50 then limits rows rather than resources, and COUNT(*) counts pairs — the header is the product, not the population.
- Reject DISTINCT as the fix. It deduplicates after the product has been built, so the planner must materialise and sort the fanned-out set before the LIMIT can apply, and it leaves any SUM or AVG in the same select list wrong.
- Rewrite both filters as semi-joins, keeping resource as the only row source: AND EXISTS (SELECT 1 FROM resource_tag rt WHERE rt.resource_id = r.resource_id AND rt.tag_id = ANY($2)) and the same shape against resource_share. A semi-join stops at the first match per resource and preserves the driving index order, so ORDER BY updated_at DESC, resource_id DESC LIMIT 50 still stops after 50 rows.
- Count with the same predicates and no join at all: SELECT count(*) FROM resource r WHERE r.tenant_id = $1 AND r.status = 'active' AND EXISTS (...) AND EXISTS (...). Nothing multiplies a resource, so the number is the population.
Follow-up
- The filter changes from 'any of these tags' to 'all of these tags'. Rewrite it and state what it costs relative to the ANY form.
- A resource can be shared with the same user twice under different permissions. Does your count change, and should it?
Explain why the owner filter ignores the listing index
The only index on resource is (tenant_id, status, updated_at DESC, resource_id DESC). A new endpoint returns one user's resources across all statuses, newest created first: WHERE tenant_id = $1 AND owner_user_id = $2 ORDER BY created_at DESC LIMIT 20. On a tenant with 2M rows it takes 900 ms and EXPLAIN shows a sort above a large scan. Explain precisely why the existing index cannot serve it, give the index that can, and state which of these the new index still will not help: owner_user_id alone across tenants; the same query ordered by updated_at. PostgreSQL 16.
Approach
- Separate the two jobs an index does. For filtering, a composite btree is seekable only on a left prefix, so with no predicate on status the scan can at best range over tenant_id and test owner_user_id per row; PostgreSQL 16 has no btree skip scan to jump the unconstrained column.
- For ordering, the index is sorted by (status, updated_at) within a tenant and not by created_at, so the LIMIT cannot stop early: every matching row is read and then sorted. That is the 'Sort Method: top-N heapsort' line, and it is why the plan reads 2M rows to answer with 20.
- Derive the replacement from the access path — equality, equality, then the ordering column: CREATE INDEX CONCURRENTLY ON resource (tenant_id, owner_user_id, created_at DESC). The scan seeks to the (tenant, owner) range and walks 20 entries in order, so the Sort node disappears along with the row-read.
- Treat INCLUDE (title, status) as conditional, not free. An index-only scan still visits the heap for any row whose page is not marked all-visible, so on a table taking 1.2k writes/second the win depends on autovacuum keeping the visibility map current, and the wider index costs more on every insert.
Follow-up
- 90% of rows are status='active'. Would a partial index WHERE status = 'active' change your answer, and for which of the three queries?
- A dashboard runs this for 40 owners in one page load. What changes about the design?
Explain the difference between dependency injection and service location in your preferred framework.
Explain the difference between dependency injection and service location in your preferred framework.
Approach
- Clarify what is being asked and what a complete answer contains.
- State your assumptions explicitly before working the problem.
- Say what you would check first and why it is the highest-information step.
- Work from the requirement backwards to the design.
Follow-up
- What assumption would you test first?
- How would you know your answer was wrong?
Describe a challenging bug you encountered in a production environment and your systematic approach to resolvi
Describe a challenging bug you encountered in a production environment and your systematic approach to resolving it.
Approach
- Clarify what is being asked and what a complete answer contains.
- State your assumptions explicitly before working the problem.
- Say what you would check first and why it is the highest-information step.
- Work from the requirement backwards to the design.
Follow-up
- What assumption would you test first?
- How would you know your answer was wrong?
How do you ensure code quality and maintainability in a large-scale project?
How do you ensure code quality and maintainability in a large-scale project?
Approach
- Clarify what is being asked and what a complete answer contains.
- State your assumptions explicitly before working the problem.
- Say what you would check first and why it is the highest-information step.
- Work from the requirement backwards to the design.
Follow-up
- What assumption would you test first?
- How would you know your answer was wrong?
Explain the benefits and trade-offs of using microservices versus monolithic architecture.
Explain the benefits and trade-offs of using microservices versus monolithic architecture.
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- State the consistency you need, and where you are willing to be stale.
Follow-up
- What breaks first when traffic grows ten times?
- How does this behave when that dependency is down for an hour?
How would you design a scalable, fault-tolerant web application hosted on AWS?
How would you design a scalable, fault-tolerant web application hosted on AWS?
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- State the consistency you need, and where you are willing to be stale.
Follow-up
- What breaks first when traffic grows ten times?
- How does this behave when that dependency is down for an hour?
What are the key considerations when moving an on-premise application to a cloud-native architecture?
What are the key considerations when moving an on-premise application to a cloud-native architecture?
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- State the consistency you need, and where you are willing to be stale.
Follow-up
- What breaks first when traffic grows ten times?
- How does this behave when that dependency is down for an hour?
How do you manage secrets and environment configurations in a secure and scalable way?
How do you manage secrets and environment configurations in a secure and scalable way?
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- State the consistency you need, and where you are willing to be stale.
Follow-up
- What breaks first when traffic grows ten times?
- How does this behave when that dependency is down for an hour?
Describe your strategy for implementing CI/CD pipelines to ensure seamless deployment cycles.
Describe your strategy for implementing CI/CD pipelines to ensure seamless deployment cycles.
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- State the consistency you need, and where you are willing to be stale.
Follow-up
- What breaks first when traffic grows ten times?
- How does this behave when that dependency is down for an hour?
Read latency spikes on a sixty-second sawtooth
The cached listing read path serves about 14k reads/second at an 85% hit rate. p99 sits at 35 ms for 57 seconds, jumps to 900 ms for 3, and repeats. During each spike the primary shows several hundred identical listing queries starting within the same millisecond, all carrying one large tenant's id. Cache entries use a 60-second TTL. Give the mechanism, the ordered checks, the fix, and the correctness hazard your fix must not introduce.
Approach
- Match the period to a configured number before theorising about load. A spike every 60 seconds against a 60-second TTL is an entry expiring, and you confirm it by correlating spike timestamps with the entry's write time rather than with the traffic curve. If the period had matched a cron or a GC interval instead, this is a different investigation.
- Establish the concurrency of the miss. Several hundred identical queries in one millisecond means the miss path has no coalescing: every request that arrives between expiry and repopulation recomputes. The herd size is that key's arrival rate times its recompute time, so at 1.2k reads/second for the hot key and a 250 ms recompute you expect about 300 concurrent misses, which matches what is observed.
- Add single-flight on the miss path so one caller per key recomputes under a short-lived lock while the rest wait for its result. Prefer stale-while-revalidate where the read tolerates it: return the expired value immediately and refresh asynchronously, which removes the latency spike rather than serialising it into a queue of waiters.
- De-synchronise the keys. Write TTLs with jitter, for example 60 seconds plus or minus 10%, so a deploy or a mass invalidation does not align every key on the same second and turn a per-key herd into a fleet-wide one.
Follow-up
- The same sawtooth appears on a key that is invalidated on write rather than expired. Is that the same bug?
- How does your answer change if the recompute takes 4 seconds instead of 250 ms?
Built from the rounds and topics Softwave Soluzioni & Tecnologie Srl candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the Softwave Soluzioni & Tecnologie Srl loop
- Write out the reported sequence: Initial Screening, Technical Evaluations, Team Engagement.
- For each round, write one sentence on what it is judging, from the description above, and mark the one you are least ready for.
Deliverable: A one-page map of the 3 reported rounds, with the weakest marked.
02Work .NET
- Spend the session on .NET, which Softwave Soluzioni & Tecnologie Srl candidates report being tested on.
- Write one worked example in .NET and time yourself on it.
Deliverable: One timed worked example in .NET.
03Work AWS
- Spend the session on AWS, which Softwave Soluzioni & Tecnologie Srl candidates report being tested on.
- Write one worked example in AWS and time yourself on it.
Deliverable: One timed worked example in AWS.
04Work Cloud Computing
- Spend the session on Cloud Computing, which Softwave Soluzioni & Tecnologie Srl candidates report being tested on.
- Write one worked example in Cloud Computing and time yourself on it.
Deliverable: One timed worked example in Cloud Computing.
05Answer out loud: Technical and Domain Expertise
- Answer aloud, timed: Explain the difference between dependency injection and service location in your preferred framework.
- Answer aloud, timed: How do you handle database connection pooling and thread safety in a high-concurrency environment?
Deliverable: Spoken answers to 2 reported Technical and Domain Expertise question(s), under time.
06Answer out loud: System Design and Cloud Architecture
- Answer aloud, timed: How would you design a scalable, fault-tolerant web application hosted on AWS?
- Answer aloud, timed: What are the key considerations when moving an on-premise application to a cloud-native architecture?
Deliverable: Spoken answers to 2 reported System Design and Cloud Architecture question(s), under time.
07Answer out loud: Behavioral and Problem Solving
- Answer aloud, timed: Tell me about a time you had to explain a complex technical concept to a non-technical stakeholder.
- Answer aloud, timed: How do you prioritize your tasks when faced with conflicting deadlines or shifting project requirements?
Deliverable: Spoken answers to 2 reported Behavioral and Problem Solving question(s), under time.
Expand any day for tasks and deliverables. Your progress is saved on this device.
Behavioural rounds judge the decision you made and what it cost.
Tell me about a time you had to explain a complex technical concept to a non-technical stakeholder.
Tell me about a time you had to explain a complex technical concept to a non-technical stakeholder.
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- Name the disagreement and how you resolved it with evidence.
Follow-up
- What would you do differently if you ran that again?
- How did you know your change caused the improvement?
How do you prioritize your tasks when faced with conflicting deadlines or shifting project requirements?
How do you prioritize your tasks when faced with conflicting deadlines or shifting project requirements?
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- Name the disagreement and how you resolved it with evidence.
Follow-up
- What would you do differently if you ran that again?
- How did you know your change caused the improvement?
Describe a situation where you disagreed with a technical decision made by a peer or manager. How did you reso
Describe a situation where you disagreed with a technical decision made by a peer or manager. How did you resolve it?
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- Name the disagreement and how you resolved it with evidence.
Follow-up
- What would you do differently if you ran that again?
- How did you know your change caused the improvement?
- 01
Tell me about a time you had to explain a complex technical concept to a non-technical stakeholder.
- 02
How do you prioritize your tasks when faced with conflicting deadlines or shifting project requirements?
- 03
Describe a situation where you disagreed with a technical decision made by a peer or manager. How did you resolve it?
How difficult are the technical interviews?
The interviews are designed to be challenging but fair. They focus on practical, real-world application of your skills rather than abstract trivia.
Softwave Soluzioni & Tecnologie Srl Software Engineer candidate reports ↗How long does the hiring process take?
While it can vary, we aim to move candidates through the process in a timely manner. You can typically expect a decision within a few weeks of your final interview.
Softwave Soluzioni & Tecnologie Srl Software Engineer candidate reports ↗Is there a focus on remote work?
Our roles are based in Lombardy or Lazio, and we prioritize a collaborative office environment. Please discuss specific hybrid or remote arrangements with your recruiter during the initial screen. Always be prepared to discuss your past projects in detail, as we value practical experience over theoretical knowledge.
Softwave Soluzioni & Tecnologie Srl Software Engineer candidate reports ↗What topics does Softwave Soluzioni & Tecnologie Srl test in interviews?
Softwave Soluzioni & Tecnologie Srl interviews most often cover SQL, Performance Optimization,.NET, Streaming data processing, and iOS Development. The exact emphasis depends on the specific role you apply for.
Softwave Soluzioni & Tecnologie Srl Software Engineer candidate reports ↗Sources & methodology 3 sources ↗
No official company page is cited. Rounds and questions come from candidate reports and PracHub editorial material; each source shows the date it was read.
- 01Softwave Soluzioni & Tecnologie Srl Software Engineer candidate reports ↗
Company-reported rounds, questions and FAQ.
Candidate reports · Accessed 2026-09-22 - 02PracHub Software Engineer practice ↗
PracHub practice material, not company-reported.
PracHub page · Accessed 2026-09-22 - 03PracHub preparation framework ↗
PracHub preparation guidance.
PracHub page · Accessed 2026-09-22
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